Results 161 to 170 of about 30,535 (208)

Clustering Users’ POIs Visit Trajectories for Next-POI Recommendation

2018
A novel recommender system that supports tourists in choosing interesting and novel points of interests (POIs) is here presented. It can deal with situations where users’ data is scarce and there is no additional information about users apart from their past POIs visits.
David Massimo, Francesco Ricci
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Geographic-categorical diversification in POI recommendations

Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, 2019
Nowadays, Recommender Systems (RSs) have been used to help users to discover relevant Points Of Interest (POI) in Location Based Social Network (LBSN), such as Yelp and FourSquare. Due to the main challenges of data sparsity and the geographic influence in this scenario, most of works about POI recommendations has only focused on improving the system's
Rodrigo Carvalho, Nícollas Silva, Luiz Chaves, Adriano C. M. Pereira, Leonardo Rocha   +4 more
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UFC: A Unified POI Recommendation Framework

Arabian Journal for Science and Engineering, 2019
With the popularity of location-based social networks, personalized points-of-interest (POIs) recommendation has become an essential online service, providing a wide variety of user preferred check-in locations, namely POIs. However, the sparsity of user-POI matrix makes it difficult to recommend unvisited POIs to users.
Jiajun Zhou, Bo Liu, Yaofeng Chen, Fuqiang Lin   +3 more
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POI Recommendation: A Temporal Matching between POI Popularity and User Regularity

2016 IEEE 16th International Conference on Data Mining (ICDM), 2016
Point of interest (POI) recommendation, which provides personalized recommendation of places to mobile users, is an important task in location-based social networks (LBSNs). However, quite different from traditional interest-oriented merchandise recommendation, POI recommendation is more complex due to the timing effects: we need to examine whether the
Zijun Yao, Yanjie Fu, Bin Liu, Yanchi Liu, Hui Xiong   +4 more
openaire   +1 more source

TGVx: Dynamic Personalized POI Deep Recommendation Model

INFORMS Journal on Computing, 2023
Personalized points-of-interest (POI) recommendation is very important for improving the service quality of location-based social network applications. It has become one of the most popular research directions in the industry and academia. However, the realization of high-quality personalized POI recommendation faces three major challenges: (i) the ...
Xiao-Jun Wang, Tao Liu, Weiguo Fan
openaire   +1 more source

Multi-factor Fusion POI Recommendation Model

2020
In the context of the rapid development of location-based social networks (LBSN), point of interest (POI) recommendation becomes an important service in LBSN. The POI recommendation service aims to recommend some new places that may be of interest to users, help users to better understand their cities, and improve users’ experience of the platform ...
Xinxing Ma, Jinghua Zhu, Shuo Zhang, Yingli Zhong   +3 more
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Exploiting Hierarchical Structures for POI Recommendation

2017 IEEE International Conference on Data Mining (ICDM), 2017
With the rapid development of location-based social networks, Point-of-Interest (POI) recommendation has played an important role in helping people discover attractive locations. However, existing POI recommendation methods assume a flat structure of POIs, which are better described in a hierarchical structure in reality.
Pengpeng Zhao, Xiefeng Xu, Yanchi Liu, Ziting Zhou, Kai Zheng, Victor S. Sheng, Hui Xiong   +6 more
openaire   +1 more source

A Multi-factor Recommendation Algorithm for POI Recommendation

2018
Point-of-Interest (POI) recommendation is an important service in Location-Based Social Networks (LBSNs). There are several approaches, such as collaborating filtering or content-based filtering, to solving the problem, but the quality of recommendation is low because of lack of personalized influencing factors for each user.
Rong Yang, Xiaofeng Han, Xingzhong Zhang
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On accurate POI recommendation via transfer learning

Distributed and Parallel Databases, 2020
Point of interest (POI) recommendation is of great value for both service providers and users. However, it is hard due to data scarcity. To this end, in this paper, we propose a transfer learning based deep neural model, which fuses valueable cross-domain knowledge to achieve more accurate POI recommendation.
Hao Zhang, Siyi Wei, Xiaojiao Hu, Ying Li, Jiajie Xu   +4 more
openaire   +1 more source

Context-Aware Personalized POI Sequence Recommendation

2019
The Point Of Interest (POI) sequence recommendation applies to scenarios like itinerary and travel route planning which belongs to the class of NP-hard problem. What’s more, the external environment like the weather, time can affect the user’s check-in behavior such as people prefer to check-in in ice cream shop when the temperature is higher.
Jing Chen, Wenjun Jiang
openaire   +1 more source